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---license: mit
task_categories:
- text-to-image
- unconditional-image-generation
language:
- en
- es
tags:
- finance
- biology
- chemistry
- code
- art
- synthetic
pretty_name: My Auto-Tune Dataset πΌοΈπ¨
size_categories:
- n>1T
---
---
~~~
# π Dataset Card for **My Auto-Tune Dataset**
---
### π **Dataset Summary**
π This dataset is designed to fine-tune models for generating high-quality images from text prompts. Whether you're into **art**, **synthetic data**, or **creative AI**, this dataset is your go-to source for automatic image generation! πποΈ
---
## 𧩠**Dataset Details**
### π **Description**
π§ This dataset includes a massive collection of text-image pairs to train and fine-tune text-to-image models. With **multi-lingual support** (English & Spanish) π, it's perfect for applications in fields such as **finance**, **biology**, **chemistry**, and even **code-based art generation**! πΈπ§¬βοΈπΎ
---
### π **Dataset Sources**
- **Repository**: [nivin-ai/faq_embeddings](https://huggingface.co/nivin-ai/faq_embeddings)
- **Paper [optional]**: Currently, there is no associated paper π.
- **Demo [optional]**: Coming soon! π§
---
## π‘ **Intended Uses**
### β
**Direct Use**
- Fine-tuning models for **text-to-image** generation π¨.
- Building **creative AI systems** for generating unique visuals πΌοΈ.
- Developing models in **art, synthetic data**, and **finance** contexts π°.
### π« **Out-of-Scope Use**
- β οΈ **Do not use** this dataset for generating harmful, explicit, or misleading content.
- Avoid applications in **real-time decision-making systems** where accuracy is critical π.
---
## ποΈ **Dataset Structure**
- **File Types**: `.jsonl` for text-image pairs ποΈ.
- **Splits**: Train and validation splits are defined as follows:
- `train/`: 80% of the data ποΈββοΈ
- `validation/`: 20% for model evaluation π§ͺ
---
## βοΈ **Dataset Creation Process**
### π― **Curation Rationale**
The dataset was developed to empower **researchers and developers** to create state-of-the-art **text-to-image generation models**. It's optimized for **large-scale projects** requiring high-quality visual outputs π.
### ποΈ **Source Data**
- **Collection Process**: Scraped from **open-source** text and image databases π.
- **Processing**: All text entries were normalized, and images were resized for consistent input dimensions πΌοΈ.
---
### βοΈ **Annotations**
- **Annotation Process**: Annotations include descriptions and metadata for images π.
- **Annotators**: Curated by experts in **AI, finance, and art** domains π.
- **Tools Used**: Hugging Faceβs `datasets` library and custom Python scripts π.
---
## π **Bias, Risks, and Limitations**
While this dataset aims to provide **neutral and creative** content, users should be aware that:
- It may contain **biases inherent** in its source data π§.
- The dataset should not be used for generating **inappropriate or offensive** content π«.
- May not be suitable for **mission-critical applications** (e.g., medical, legal, or financial advice) β οΈ.
---
### π **Recommendations**
- Always evaluate model outputs for **biases** and **inaccuracies** before deployment.
- Use responsibly, especially if integrating with sensitive applications πΌ.
---
## π **Citations**
If you use this dataset, please cite:
```bibtex
@misc{my_auto_tune_dataset_2024,
title={My Auto-Tune Dataset},
author={Derrick Adkison, Kumplex Media Holdings Group LLC},
year={2024},
url={https://huggingface.co/nivin-ai/faq_embeddings},
license={MIT}
}
~~~
---
## π Contact Information
Author: Derrick Adkison
Organization: Kumplex Media Holdings Group LLC
Email: [email protected]
Alternate Email: [email protected]
Phone: +1 253-293-2802 βοΈ
---
π Glossary
---
π More Information
For any questions, open an issue on the GitHub repository or contact us directly π§.
---
π€ Dataset Card Authors
Derrick Adkison
Contributors: Hugging Face Community π§βπ€βπ§
---
This dataset card covers all essential fields and includes fun, emoji-filled explanations to make it engaging for users. Let me know if you need more tweaks or additional fields!
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